Exam NCA-GENM Topic 1 Question 244 Discussion

Actual exam question for NVIDIA's NCA-GENM exam
Question #: 244
Topic #: 1

Consider a scenario where you are developing a multimodal A1 system to translate sign language videos into text. The system utilizes a CNN for processing video frames and an RNN for generating the text sequence. During evaluation, you observe that the system struggles to accurately translate signs that involve complex hand movements or subtle facial expressions. What are the MOST effective strategies to improve performance in this specific scenario? (Select TWO)

A. Reduce the frame rate of the input video to decrease computational load. B. Increase the depth of the CNN to capture more fine-grained visual features. C. Incorporate a 3D CNN architecture to better capture spatial-temporal information from the video. D. Replace the RNN with a simpler feed forward neural network for faster processing. E. Augment the training data with variations of the sign language videos, including different camera angles, lighting conditions, and signers.

Suggested Answer: C,E Vote an answer

3D CNNs are designed to capture spatial-temporal information, which is essential for recognizing complex hand movements. Data augmentation helps the model generalize to different conditions and variations in signing style. Reducing frame rate (A) would likely worsen performance. Replacing the RNN with a feed forward network (D) would remove the ability to model sequential information, which is critical for translation. Increasing the depth of the CNN (B) might help, but a 3D CNN is more directly suited to the task.

by Novia at Sep 29, 2025, 09:52 AM

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